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Tackling Climate Change with Machine Learning
Event Summary
Machine learning can be a useful tool in helping society reduce greenhouse gas emissions and adapt to a changing climate. In this workshop, Prof. David Rolnick will explore opportunities and challenges in machine learning for climate action, from designing new electrocatalysts to monitoring biodiversity. He will also consider how machine learning is used in ways that contribute to climate change, and how to better align the use of machine learning overall with climate goals.
Snacks and other refreshments will be served.
The workshop is free of charge, open to the public, and will be held in person.
The AI and Climate Change workshop series is organized by the Penn Program on Regulation and is made possible in part by funding from the Environmental Innovations Initiative. Co-sponsors include the Kleinman Center for Energy Policy, Warren Center for Network and Data Sciences, and Wharton Climate Center.
David Rolnick
Assistant Professor, McGill UniversityDavid Rolnick is Assistant Professor and Canada CIFAR AI Chair in the School of Computer Science at McGill University and the Mila-Quebec AI Institute.
Cary Coglianese
Edward B. Shils Professor of LawCary Coglianese is the Edward B. Shils Professor of Law and Professor of Political Science at the Carey School of Law. He also is the director of the Penn Program on Regulation.
